Abstract
AbstractPostharvest handling tasks include fruit grading and minimizing loss. Fruits are often packaged into grades based on size and mass for uniformity and proper handling. Losses caused by mechanical damage can be reduced by understanding the fruit's response to loads. Papaya's (cv. Exotica) irregular shape and short shelf‐life are important factors for proper handling. This study aimed to develop a model for papaya mass based on geometric properties and to characterize its mechanical behavior when compressed along its major axis. For mass prediction, single‐ and multiple‐variable regression models using papaya's geometrical variables were developed. Despite its irregular shape, similar performance was observed in the best single‐ and multiple‐variable mass models (R2 ≈ 0.95, RMSE ≈ 82 g). However, the single‐variable model is likely more practical because only two axial lengths are needed and can be extracted from 2D images. For papaya's mechanical behavior, the results for elastic properties indicate some variations (p > 0.05) in elastic modulus, and failure stress and strain along the major axis, while results for viscoelastic properties indicate significant variation (p < 0.05) in the relaxation moduli. Overall, the bottom section is less resistant to deformation compared to the top. Therefore, reducing compression in the section could potentially reduce damage. Using the mechanical properties described here in computer simulation studies may provide more detailed load distribution. Mass modeling can aid the automation of papaya grading, while mechanical response characterization provides valuable information for designing postharvest handling systems.Practical ApplicationsPostharvest handling tasks include fruit grading and minimizing loss. Fruits are often packaged into grades based on size and mass for uniformity and proper handling. Losses caused by mechanical damage may be reduced by understanding the fruit's response to loads. Papaya's irregular shape and short shelf‐life are important factors for proper postharvest handling. Mass modeling can assist the automation of papaya sorting, while characterizing its mechanical response can assist the design of postharvest handling systems. The mass model result indicates that papaya's mass (cv. Exotica) can be predicted using two axial lengths, which can be easily obtained using 2D images. The advantage is that this task can be combined with other tasks using imaging data. While the mechanical properties of papaya indicate that its bottom section is more susceptible to deformation compared to the top when they are stored in an environment with minimal movements over an extended period. Therefore, in this setup, applying the compression load at the top section while minimizing compression load at the bottom may be more effective in preventing and minimizing mechanical damage.
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